Scalable base station switching framework for green cellular networks

With the recent unprecedented growth in the wireless market, network operators are obliged not only to find new techniques including dense deployment of base stations (BSs) in order to support high data rate services and high user density, but also to reduce the operating costs and energy consumption of various network elements. To solve these challenges, powering down certain BSs during low-traffic periods, so-called BS sleeping, has emerged as an effective green communications paradigm. While BS sleeping offers the potential to significantly lower energy consumption, it also raises many challenges, since when a BS is switched off, this can lead to, for example, coverage holes, sudden degradation in quality of service (QoS), higher transmit power dissipation in off-cell mobile stations (MSs), an inability to rapidly power up/down equipment and finally, a failure to uphold regulatory requirements. In order to realise greener network designs which both maximise energy savings whilst guaranteeing QoS, innovative BS switching mechanisms need to be developed. This thesis presents a novel BS switching framework which improves energy efficiency (EE) in comparison with existing approaches, while guaranteeing the minimum QoS and seamless services. The major technical contributions in this framework are: i) a new BS to relay station (RS) switching model where certain BSs are switched to RS mode rather than being turned off, firstly using a fixed threshold based switching algorithm utilizing temporal traffic diversity, and ii) then subsequently by means of an adaptive threshold by exploiting the inherently asymmetric traffic profile between cells, i.e., by exploiting both the temporal and spatial traffic diversity; iii) a traffic-and-interference-aware BS switching strategy that considers the impact of inter-cell interference in the decision making process to dynamically determine the best BS set to be kept active for improved EE; and finally iv) a novel scalable multimode BS switching model which enables each BS to operate in different power modes i.e., macro/micro/sleep to explore energy savings potential even at higher traffic conditions. The thesis findings conclusively confirm this new BS switching framework provides significant EE improvements from both BS and MS perspectives, under diverse network conditions and represents a notable step towards greener communications

Energy savings using an adaptive base station-to-relay station switching paradigm

Applying a Base Station (BS) sleep approach during low traffic periods has recently been advocated as a strategy for reducing energy consumption in cellular networks. The complete switching off of certain BS however, can lead to coverage holes and severe performance degradation in terms of off-cell user throughput, greater transmit power dissipation in both the up and downlinks, and more complex interference management. This paper presents a novel cellular network energy saving model in which certain BS rather being turned off are switched to Relay Station (RS) mode during low traffic periods. The switched RS and other shared RS deployed at the cross border of each cell are responsible for upholding the same quality of service (QoS) provision as when all BS are active. A centralised adaptive switching threshold algorithm is also introduced to undertake the switching decision, instead of using a fixed threshold. Simulation results confirm the new BS-RS Switching model using an adaptive threshold can reduce network energy consumption by more than half, as well as improving off-cell users’ throughput

Dynamic spectrum access based on cognitive radio within cellular networks

Overlay transmissions in cognitive radio (CR) permit a secondary system to use spectrum concomitantly with a primary system, though adopting this spectrum sharing strategy presents a number of challenges, such as the requirement for a secondary user to have a priori knowledge as side information about the primary user. In this paper, a cognitive cellular network is proposed which uses an overlay approach to dynamically share its radio resource by incorporating cognition, leading to enhanced cell capacity. To compensate for the interference caused by the overlay, cognitive base stations use robust dirty-paper coding in combination with variable transmission powers, which are set depending upon the location of the mobile stations. A detailed performance analysis is presented to corroborate the improved spectrum utilization achieved using this technique

Traffic-and-interference aware base station switching for green cellular networks

Base station (BS) sleeping in cellular networks has emerged as a promising solution for more energy efficient communications, concomitant with lowering the network carbon footprint. Switching off specific BS entirely however, can lead to coverage holes and severe performance degradation. To avoid coverage holes, the transmit power of neighbouring BS must be commensurately increased, which can cause higher interference to other cell users. Recently a BS-RS (relay station) switching model has been proposed where the BS changes operating mode to a RS during off-peak periods rather than being completely turned off. This paper presents a traffic-aware and traffic-and-interference aware switching strategy for both the BS sleeping and BS-RS switching paradigms, which dynamically establishes the conditions for a BS to alter its working mode. The switching is based upon a dynamic traffic threshold allied with the received BS interference level. Analysis corroborates both new algorithms significantly improve network energy efficiency, while upholding the requisite quality of service provision

LTE Mobile Communication Systems: Channel Estimation for Uplink

Fast mobile broadband is becoming a reality. It is estimated that almost 3.4 billion people will have broadband by 2014 (about 80 percent will be mobile broadband subscribers). LTE is one of the lastest technology for delevering services to those huge amount of subscribers. This project focuses on the channel estimation for uplink of the UMTS LTE where single carrier-frequency division multiple access (SC-FDMA) technique is utilized as multiple access air interfaces. Based on working assumptions of 3GPP, this project estimates and predicts time-varying nature (Doppler effects) of the channel for the UMTS LTE (uplink) by different low-complexity methods. The channel estimation is done in both the temporal-and-frequency-domain. The estimation of channel in frequency-domain is based on Interpolation method, Least Square (LS) method and Wiener filtering or Linear Minimum Mean Square Error (LMMSE) method. The estimation of channel in temporal-domain is done using linear Interpolation. The performance of all these schemes are compared by measuring bit-error-rate (BER) for different signal-to-noise ratio (SNR) with QAM-16 modulation on Rayleigh fading channel based on Jakes’ model